Data Scientist, Algorithms - Dynamic Pricing

About the role

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

The Marketplace team at Lyft is responsible for accelerating the growth of the business while simultaneously delivering on key business and financial metrics, and Dynamic Pricing & Offer Selection is an integral part of that. Our team is the dynamic pricing team responsible for leveraging both real-time and historical data to set prices for every single ride at Lyft while balancing prices and ETAs to better serve our riders’ needs.

We are looking for fast learning, data-driven individuals who are passionate about tackling these open-ended problems in pricing theory and making a large, positive impact in the business. In this role, you will work closely with Product and Engineering on a cross-functional team to prototype and build end-to-end dynamic pricing models that can operate at scale. In addition, you will be expected to leverage your domain knowledge and influence existing and future roadmaps to help Lyft continue to deliver a better experience for riders and drivers.

Responsibilities:

- Partner with other scientists, colleagues in the pricing team, and with external teams to formalize problems mathematically and within the business context

- Perform complex data analysis to gain a deeper understanding of problems by identifying their root causes

- Develop and fit statistical, machine learning, or optimization models

- Write production code; collaborate with Software Engineers to ship models to production

- Design and implement both simulated and live experiments

- Analyze experimental and observational data; facilitate launch decisions

- Communicate findings to a broad audience consisting of Product, Engineering, and executive leadership

Experience:

- Data Scientist with experience in Machine Learning, Statistics, Economics, or other quantitative fields

- M.S. or Ph.D. in Computer Science, Economics, Statistics, Mathematics, or other quantitative fields

- 1-4+ years of professional experience for PhDs or 3-5+ years for Master’s in a Data Science role

- Passion for solving unstructured and non-standard mathematical problems

- End-to-end experience with data, including querying, aggregation, analysis, and visualization

- Proficiency with Python, or another interpreted programming language like R or Matlab

- Proficiency in SQL - able to write structured and efficient queries involving multiple large data sets

- Ability to collaborate and communicate with others to solve a problem

- Strong oral and written communication skills, and ability to collaborate with cross-functional partners

- Experience in causal inference, LTV modeling, econometrics, or user choice modeling preferred

Benefits: